The Autoimmunity Centers of Excellence (ACE) seeks to improve the understanding and treatment of autoimmune diseases. Our Bioinformatics Core will serve a vital role in achieving this goal by aiding in the processing and analysis of the clinical, genomic, and immunological data. For this it will rely on established expertise and resources covering a wide range of areas essential for the success of ACE: 1) State of the art IT infrastructure and software development expertise; 2) HT Sequencing data processing pipeline; 3) Clinical data collection infrastructure and database; 4) Laboratory information and sample tracking database; 5) Data integration and sharing software; 6) Unique data mining and interpretation solutions; 7) Biostatistics expertise applied to longitudinal data analysis and biomarker discovery; 8) Sharing of data and expertise in the context of multi-center projects. We have developed this expertise working over the years on a number of translational research projects employing systems approaches and involving patients with autoimmune and infectious diseases. Most recently this wide spectrum of bioinformatics expertise was showcased in journal Immunity with our work investigating responses to commonly used vaccines in which primary data and analysis results have been made available to readers in an interactive format. By providing a global perspective, systems approaches can offer unique mechanistic insight and this work illustrates our efforts to extend the impact of systems studies well beyond the publication of the primary results. SPECIFIC AIM #1: To expand upon the capabilities of the BIIR's gene expression browser to support all data types generated from each project. The Gene Expression Browser currently supports, links, and annotates demographic, clinical, microarray, and flow cytometry variables. Deep sequencing data generated from each project will be added to this list. SPECIFIC AIM #2: To support each project by processing and integrating clinical, genomic and other immunological data into BIIR's Gene Expression Browser for the purpose of producing accurate, efficient, and reproducible bioinformatics analyses between and among the disparate data types.